Mr. Frank Iannarilli Profile

Frank Iannarilli

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Publications (13)

Proceedings Article | 9 January 2002 Paper

Development of a combined bidirectional reflectance and directional emittance model for polarization modeling

John Conant, Frank Iannarilli

Proceedings Volume 4481, (2002) https://doi.org/10.1117/12.452890

KEYWORDS: Bidirectional reflectance transmission function, Reflectivity, Polarization, Reflection, 3D modeling, Specular reflections, Thermal modeling, Diffuse reflectance spectroscopy, Refractive index, Visible radiation

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Proceedings Article | 18 October 2001 Paper

Passive IR polarimetric hyperspectral imaging contributions to multisensor humanitarian demining

Frank Iannarilli, Herman Scott, Stephen Jones

Proceedings Volume 4394, (2001) https://doi.org/10.1117/12.445486

KEYWORDS: Polarimetry, Reflectivity, Infrared imaging, Land mines, Polarization, Mining, Hyperspectral imaging, Infrared detection, Sensors, Thermography

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Proceedings Article | 15 November 2000 Paper

Snapshot LWIR hyperspectral polarimetric imager for ocean surface sensing

Frank Iannarilli, Joseph Shaw, Stephen Jones, Herman Scott

Proceedings Volume 4133, (2000) https://doi.org/10.1117/12.406635

KEYWORDS: Polarimetry, Modulation, Sensors, Polarization, Crystals, Modulators, Microwave radiation, Infrared sensors, Infrared imaging, Imaging systems

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Proceedings Article | 2 August 1999 Paper

Imaging infrared polarimetry: initial results and potential in detection of scatterable mines and surface disturbances

Herman Scott, Stephen Jones, Frank Iannarilli

Proceedings Volume 3710, (1999) https://doi.org/10.1117/12.356999

KEYWORDS: Polarimetry, Polarization, Mining, Long wavelength infrared, Reflectivity, Land mines, Sensors, Infrared imaging, Staring arrays, Hyperspectral imaging

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Proceedings Article | 26 July 1999 Paper

Polarimetric-spectral intensity modulation (P-SIM): enabling simultaneous hyperspectral and polarimetric imaging

Frank Iannarilli, Stephen Jones, Herman Scott, Paul Kebabian

Proceedings Volume 3698, (1999) https://doi.org/10.1117/12.354549

KEYWORDS: Polarimetry, Sensors, Modulation, Hyperspectral imaging, Modulators, Wave propagation, Polarization, Remote sensing, Wave plates, Spatial resolution

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Proceedings Article | 14 July 1999 Paper

Quantifying key trade-off between IR polarimetric discriminability versus pixel resolution against complex targets

Frank Iannarilli, John Conant

Proceedings Volume 3699, (1999) https://doi.org/10.1117/12.352965

KEYWORDS: Polarimetry, Polarization, Bidirectional reflectance transmission function, Sensors, Reflection, Infrared signatures, Dielectric polarization, Reflectivity, Image resolution, Infrared imaging

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Proceedings Article | 10 February 1999 Paper

Hyperspectral IR polarimetry with applications in demining and unexploded ordnance detection

Herman Scott, Stephen Jones, Frank Iannarilli, Kurt Annen

Proceedings Volume 3534, (1999) https://doi.org/10.1117/12.339008

KEYWORDS: Polarimetry, Polarization, Long wavelength infrared, Mining, Reflectivity, Sensors, Land mines, Hyperspectral imaging, Staring arrays, Infrared imaging

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Proceedings Article | 20 June 1995 Paper

Multispectral IR signature polarimetry for detection of mines and unexploded ordnance (UXO)

Malcolm LeCompte, Frank Iannarilli, Davis Nichols, Robert Keever

Proceedings Volume 2496, (1995) https://doi.org/10.1117/12.211315

KEYWORDS: Polarization, Land mines, Polarimetry, Infrared signatures, Mining, Signal to noise ratio, Coating, Solar radiation models, Infrared imaging, Reflectivity

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Proceedings Article | 1 September 1991 Paper

End-to-end model for detection performance evaluation against scenario-specific targets

Frank Iannarilli, Martin Wohlers

Proceedings Volume 1488, (1991) https://doi.org/10.1117/12.45805

KEYWORDS: Infrared search and track, Systems modeling, Clouds, Sensors, Performance modeling, Atmospheric modeling, Thermal modeling, Infrared imaging, Signal processing, Infrared signatures

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Proceedings Article | 1 August 1991 Paper

End-to-end scenario-generating model for IRST performance analysis

Frank Iannarilli, Martin Wohlers

Proceedings Volume 1481, (1991) https://doi.org/10.1117/12.45655

KEYWORDS: Infrared search and track, Clouds, Sensors, Performance modeling, Systems modeling, Atmospheric modeling, Signal processing, Data modeling, Data processing, Target detection

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Proceedings Article | 1 July 1991 Paper

Dynamic end-to-end model testbed for IR detection algorithms

Frank Iannarilli, Martin Wohlers

Proceedings Volume 1483, (1991) https://doi.org/10.1117/12.45731

KEYWORDS: Infrared search and track, Systems modeling, Performance modeling, Clouds, Sensors, Atmospheric modeling, Signal processing, Device simulation, Image processing, Detection and tracking algorithms

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Proceedings Article | 1 July 1991 Paper

Comparison of three efficient-detail-synthesis methods for modeling using under-sampled data

Frank Iannarilli, Martin Wohlers

Proceedings Volume 1486, (1991) https://doi.org/10.1117/12.45775

KEYWORDS: Sensors, Cameras, Spatial frequencies, Fractal analysis, Data modeling, Detector arrays, Modulation transfer functions, Image sensors, Performance modeling, Automatic target recognition

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Synthetic scene generation models depend on the repeated evaluation or iteration of often computationally expensive functions to create 'texture' or structure in a modeled natural scene. The computational burden of 'texture' function evaluation is dependent upon the spatial frequency response characteristics of the optical system through which the modeled scene is to be 'propagated.' All real 'cameras' utilize detector elements of finite size to transduce the resulting MXN pixels of the image. Two general situations arise in modeling the effects of cameras (sensors) on the imaged scene. The first is the 'oversampled' case where the Nyquist frequency of the detector spacing exceeds the cutoff of the optics transfer (aperture) function. The 'undersampled' case is when such Nyquist frequency is below the aperture cutoff spatial frequency, which results in aliasing. The application of brute force in the oversampled case results in MXN scene 'texture' function evaluations, while for the undersampled case, (mM)X(nN) (m, n > 1) points are required. Several computationally efficient methods significantly reduce the stated brute force computational burden for these two cases. This paper discusses three such methods. For the oversampled case, a correct and efficient method is 2D sample 'interpolation,' in the multirate digital signal processing sense. This method expressly avoids signal aliasing caused by simpler but inappropriate bilinear interpolation of the sparser set of (mM)+(nN) (m, n fractions < 1) scene samples onto the MXN imaged scene. The second and third techniques discussed are applicable to the undersampled case. Each relies upon MXN scene 'texture' function evaluations. The second technique extrapolates the frequency spectrum of the MXN grid with a synthetic spectrum beyond Nyquist which follows the 1/f(beta ) decrease in power typical of natural (fractal) textures. The third technique, 'fractal interpolation,' operates in the spatial domain where spatial detail, generated from the computed ('texture' function) MXN grid onto a larger (nM)X(nN) grid, is synthesized at the same local fractal dimension as that of the MXN 'undersampled' data. In both cases, the synthesized frequencies above the camera Nyquist are 'folded back' in the spectral domain to approximate the aliasing of spatial frequencies into the transduced image.

Proceedings Article | 29 January 1991 Paper

Sharc, the atmospheric radiation and transmittance code for altitudes from 50 to 300 km

F. Iannarilli

Proceedings Volume 1725, 172509 (1991) https://doi.org/10.1117/12.2300209

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Showing 5 of 13 publications

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